code: def test_too_short_utterance(input_conf, inputs):
      input_size = 20
  
      body_conf = [
          {
              "block_type": "conformer",
              "hidden_size": 4,
              "linear_size": 2,
              "conv_mod_kernel_size": 3,
          }
      ]
  
      encoder = Encoder(input_size, body_conf, input_conf=input_conf)
  
      sequence = torch.randn(
          len(inputs), inputs[0], input_size, requires_grad=True
      )
      sequence_len = torch.tensor(inputs, dtype=torch.long)
  
      with pytest.raises(TooShortUttError):
          _ = encoder(sequence, sequence_len)
  
file_path: espnet/test/espnet2/asr_transducer/test_encoder.py
imports: import pytest
  import torch
  from espnet2.asr_transducer.encoder.encoder import Encoder
  from espnet2.asr_transducer.utils import TooShortUttError
label_desc: Use image node_id 4 for calling a global function with example usage: test_too_short_utterance(input_conf, inputs) without return types